An iterative Segmentation Algorithm for Audio Signal Spectra Depending on Local Centers of Gravity
Modern music production and sound generation often relies on manipulation of pre-recorded pieces of audio, so-called samples, taken from a huge database. Consequently, there is a increasing request to extensively adapt these samples to any new musical context in a flexible way. For this purpose, advanced digital signal processing is needed in order to realize audio effects like pitch shifting, time stretching or harmonization. Often, a key part of these processing methods is a signal adaptive, block based spectral segmentation operation. Hence, we propose a novel algorithm for such a spectral segmentation based on local centers of gravity (COG). The method was originally developed as part of a multiband modulation decomposition for audio signals. Nevertheless, this algorithm can also be used in the more general context of improved vocoder related applications.